A key misconception in industrial transformation and three ways to help avoid the trap
For more than a decade the industrial landscape has been inundated with grandiose promises to see massive improvement in operations via Digital Transformation (Industry 4.0, Smart Manufacturing, or any other litany of buzzwords). Connect your devices, collect your data, pump it to the cloud, hand the data to the data scientists and through the power of Machine Learning (ML) and Artificial Intelligence (AI), we get transformation. It’s an alluring story, but it’s misguided and many that are piloting these solutions are not seeing the value in moving to larger implementations. Vendors call it “pilot purgatory” but analysts such as LNS Research have extensively surveyed manufacturing organizations do not indicate they’re stuck in purgatory. They suggest that while the technology is interesting, it’s not sufficient to deliver the improvements they were promised.
There are three keys that differentiate those who succeed and those who stagnate. Clear vision and purpose from the top that cascades down into an executable plan, inspiring a culture of quality and change, and using a validated set of data to build improved operational processes.
While we will go into much deeper analysis on each topic, for now, let’s look at these three pillars of transformation success quickly and discuss how you can bring them to the forefront in your organization.
C-suites and boards are justifiable enamored with transformation. Executed properly, these endeavors move all the executive levers in the proper direction. The challenge is vision translating into execution. Ultimately, the vision needs to be turned into an actionable plan that engage multiple stakeholders and layers in an organization, specifically including those on the front line of operations, quality, maintenance and reliability, and supply chain, to name a few. Having a top-down and bottom-up view is essential to success.
Nobody truly likes to change, but it’s happening all around us. Recognizing that it’s going to happen with or without you, having input into the process creates the opportunity to feel better about the outcome. Engaging with management and front-line colleagues, gathering feedback, and engaging that feedback to help eliminate outdated methods and tasks helps create a more engaged environment. Removing the stigma that change is going to be pushed on you and will lead to pain requires a full commitment from the team impacted. Starting small to gain trust can go a long way to building a sustainable program and momentum.
A third key element to success is having the right data. We hear a lot about ML and AI being able to infer, and frankly, picturing some data scientists recalls images of a hoarder with magazines, newspapers, and books everywhere. Try finding what you’re looking for in that clutter. All that data also leads to a lot of potential bad findings, particularly because many data feeds are incomplete or not properly understood. Leveraging content that is validated and tested can help shorten time to value because you know what you’re referencing is accurate. No more trying to find a needle in a haystack, but instead taking information that has been researched and collected by subject matter experts over years of practical use.
While having all three pillars is ideal, it will likely take effort to achieve. Ensuring the proper data is present can be a potentially easy win allowing you to use the proper analytics and decision trees to help drive improvement. This can lead to getting buy in for change and for mid and senior managers to throw more plans for execution against the C-suite’s vision. Follow us on LinkedIn to learn more about actionable ways to transform successfully.
